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<p>Artificial intelligence medical devices are increasingly deployed in clinical practice, yet practical approaches to post-deployment monitoring remain poorly defined. We present a structured, decision-oriented approach to monitoring within healthcare institutions, grounded in our own deployment experience. By framing surveillance as a set of interdependent decisions, this model supports effective performance assessment and governance-linked corrective action, enabling safer and more accountable integration of AI into routine clinical care.</p>

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Beyond Validation: Operationalising Post-Deployment Surveillance of AI Medical Devices in Clinical Practice

  • 期刊论文

  • 发表日期：

    2026年6月19日

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  • Jesus A. Perdomo Lampignano,
  • Aditya Kale,
  • Shamie Kumar,
  • Dhruv Shah,
  • Bhargava Reddy,
  • David J. Lowe

摘要

Artificial intelligence medical devices are increasingly deployed in clinical practice, yet practical approaches to post-deployment monitoring remain poorly defined. We present a structured, decision-oriented approach to monitoring within healthcare institutions, grounded in our own deployment experience. By framing surveillance as a set of interdependent decisions, this model supports effective performance assessment and governance-linked corrective action, enabling safer and more accountable integration of AI into routine clinical care.